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All HBS Web
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- Faculty Publications (1,419)
- January 2024
- Case
Flashfood: The Magic of Commitment
By: Reza Satchu and Patrick Sanguineti
Josh Domingues had accomplished what countless young entrepreneurs long to achieve: founding a promising company that aspires to make the world a tangibly better place. Shocked to learn that international food waste cumulatively amounted to the world’s third largest...
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Keywords:
Entrepreneur;
Founder;
Startup;
Business Model;
Business Startups;
Food;
Applications and Software;
Mission and Purpose;
Environmental Sustainability;
Canada
Satchu, Reza, and Patrick Sanguineti. "Flashfood: The Magic of Commitment." Harvard Business School Case 824-131, January 2024.
- 2024
- Working Paper
Contributing to Growth? The Role of Open Source Software for Global Startups
By: Nataliya Langburd Wright, Frank Nagle and Shane Greenstein
Does participating in open source software (OSS) communities spur entrepreneurial growth? More
efficiently developing shared code, learning from what the OSS community has developed, and
shaping the direction of massive projects, such as those linked to frameworks...
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Keywords:
Applications and Software;
Open Source Distribution;
Entrepreneurship;
Business Growth and Maturation;
Human Capital;
Valuation;
Corporate Strategy
Wright, Nataliya Langburd, Frank Nagle, and Shane Greenstein. "Contributing to Growth? The Role of Open Source Software for Global Startups." Harvard Business School Working Paper, No. 24-040, January 2024.
- January 2024 (Revised February 2024)
- Case
OpenAI: Idealism Meets Capitalism
By: Shikhar Ghosh and Shweta Bagai
In November 2023, the board of OpenAI, one of the most successful companies in the history of technology, decided to fire Sam Altman, its charismatic and influential CEO. Their decision shocked the corporate world and had people wondering why OpenAI had designed a...
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Keywords:
AI;
AI and Machine Learning;
Governing and Advisory Boards;
Ethics;
Strategy;
Technological Innovation;
Leadership
Ghosh, Shikhar, and Shweta Bagai. "OpenAI: Idealism Meets Capitalism." Harvard Business School Case 824-134, January 2024. (Revised February 2024.)
- January 2024 (Revised May 2024)
- Case
Private 5G Networks
By: Andy Wu and Maggie Yang
In the late 2010’s, 5G emerged as a new standard in communication technology. 5G was designed to enable ultra-reliable low-latency communications (URLLC), massive machine-type communication (MMTC), and enhanced mobile broadband (EMBB) (see Exhibit 1 for a detailed...
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Keywords:
5G;
Communication Technology;
Mobile and Wireless Technology;
Technological Innovation;
Innovation Strategy;
Telecommunications Industry
Wu, Andy, and Maggie Yang. "Private 5G Networks." Harvard Business School Case 724-430, January 2024. (Revised May 2024.)
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its...
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Keywords:
Investor Relations;
Forecasting;
Machine Learning;
Artificial Intelligence;
Apparel;
Corporate Finance;
Forecasting and Prediction;
AI and Machine Learning;
Digital Transformation;
Apparel and Accessories Industry;
United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM...
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Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
- December 2023 (Revised February 2024)
- Case
Generative AI and the Future of Work
By: Christopher Stanton and Matt Higgins
Generative AI seemed poised to reshape the world of work, including the higher-wage, white-collar jobs typically pursued by MBA graduates. Informed by the latest research, this case explores generative AI's potential impacts on work, productivity, value creation, and...
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Keywords:
AI;
Future Of Work;
Labor Market;
AI and Machine Learning;
Labor;
Value Creation;
Performance Productivity;
Technology Industry;
United States
Stanton, Christopher, and Matt Higgins. "Generative AI and the Future of Work." Harvard Business School Case 824-130, December 2023. (Revised February 2024.)
- December 2023
- Case
Robert McNamara: Changing the World
By: Robert Simons and Shirley Sun
This case traces the life of Robert McNamara from Harvard Business School to Ford Motor Company to the U.S. Department of Defense. McNamara excelled in every job along the way: becoming the youngest-ever professor at Harvard Business School, the first non-family...
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Keywords:
Performance Measurement;
Leadership;
Business Education;
Military;
Leadership Development;
Values and Beliefs;
Personal Characteristics;
Leadership Style;
Success;
Business and Government Relations;
Power and Influence
Simons, Robert, and Shirley Sun. "Robert McNamara: Changing the World." Harvard Business School Case 124-036, December 2023.
- December 2023
- Teaching Note
Buurtzorg
By: Ethan Bernstein and Tatiana Sandino
Teaching Note for HBS Case No. 122-101. As co-founders of home nursing company Buurtzorg, Jos de Blok and Gonnie Kronenberg prized both self-management and organizational learning. Buurtzorg’s 10,000 nurses across 950 neighborhood nursing teams in the Netherlands were...
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- December 15, 2023
- Article
What Every Leader Needs to Know About Carbon Credits
By: Varsha Ramesh Walsh and Michael W. Toffel
Many companies have begun to look into credits to offset their emissions as a way to support their net zero goals as their target years get closer and closer. As it stands, the carbon credit market is too small to bear the brunt of reducing companies’ impacts on the...
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Keywords:
Carbon Credits;
Climate;
Accounting;
Carbon Offsetting;
Carbon Abatement;
Carbon Emissions;
Carbon Footprint;
Climate Change;
Environmental Accounting;
Environmental Regulation
Ramesh Walsh, Varsha, and Michael W. Toffel. "What Every Leader Needs to Know About Carbon Credits." Harvard Business Review Digital Articles (December 15, 2023).
- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which...
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Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- December 2023
- Background Note
Organizational Learning
By: Willy Shih
This is a background note that surveys part of the extensive literature on organizational learning. The focus is on learning from experiences, how those learnings get translated into organizational routines and processes, and how that can also lead to getting stuck in...
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- December 2023
- Case
Monsters in the Machine? Tackling the Challenge of Responsible AI
By: Paul M. Healy and Debora L. Spar
In November of 2022, the small tech company OpenAI released ChatGPT, an artificial intelligence chatbot which quickly captured the public’s imagination—becoming the world’s fastest-growing consumer application within months of its release. Though observers from across...
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Keywords:
Technological Innovation;
AI and Machine Learning;
Ethics;
Governing Rules, Regulations, and Reforms;
Technology Adoption;
Corporate Social Responsibility and Impact;
Technology Industry;
United States;
European Union;
China
Healy, Paul M., and Debora L. Spar. "Monsters in the Machine? Tackling the Challenge of Responsible AI." Harvard Business School Case 324-062, December 2023.
- December 2023
- Article
Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency
By: Gunther Glenk, Philip Holler and Stefan Reichelstein
Widespread adoption of hydrogen as an energy carrier is widely believed to require continued advances in Power-to-Gas (PtG) technologies. Here we provide a comprehensive assessment of the dynamics of system prices and conversion efficiency for three currently prevalent...
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Keywords:
Clean Technology;
Green Hydrogen;
Carbon Emissions;
Decarbonization;
Learning By Doing;
Environment;
Energy;
Environmental Accounting;
Environmental Management;
Sustainable Cities;
Cost Accounting;
Innovation and Management;
Technology Adoption;
Energy Policy;
Engineering;
Green Technology;
Energy Industry;
Utilities Industry;
Industrial Products Industry;
Manufacturing Industry;
Transportation Industry;
North America;
South America;
Africa;
Europe;
Asia
Glenk, Gunther, Philip Holler, and Stefan Reichelstein. "Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency." Energy & Environmental Science 16, no. 12 (December 2023): 6058–6070.
- 2023
- Article
Balancing Risk and Reward: An Automated Phased Release Strategy
By: Yufan Li, Jialiang Mao and Iavor Bojinov
Phased releases are a common strategy in the technology industry for gradually releasing new products or updates through a sequence of A/B tests in which the number of treated units gradually grows until full deployment or deprecation. Performing phased releases in a...
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Li, Yufan, Jialiang Mao, and Iavor Bojinov. "Balancing Risk and Reward: An Automated Phased Release Strategy." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,...
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Keywords:
Large Language Model;
AI and Machine Learning;
Analytics and Data Science;
Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 2023
- Book
Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow
By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing
This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business...
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Huang, Ken, Yang Wang, Feng Zhu, Xi Chen, and Chunxiao Xing, eds. Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow. Springer, 2023.
- 2023
- Article
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models
By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong
While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for...
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Keywords:
AI and Machine Learning
Lakkaraju, Himabindu, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, and Haoyi Xiong. "M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training...
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Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance...
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Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).